One of the newer capabilities in Siemens PLM vision is Fourth Generation Design (4GD). This underlying technology in Teamcenter specifically addresses the needs of users in industry segments like shipbuilding and automotive where they are dealing with highly complex products, made up of tens of thousands of parts and assemblies and where there is a density of design in terms of volume and number of configurations and variations, Paul Sicking, Siemens PLM Software's senior vice president and chief technology officer, said in an interview.
4GD's ability to help users quickly find subsets of data related to their specific task and engineering discipline is especially tailored to address the challenges of highly complex products like tankers. (Source: Siemens PLM Software)
The problem 4GD is addressing, Sicking told us, is helping users quickly find subsets of data related to their specific task and engineering discipline without having to load the entire assembly or even product, especially when that product is something as massive and complex as a nuclear submarine or tanker. One example showcased a meta data search on a multi-disciplinary vehicle 3D model using criteria such as a specific system (for example, show only the suspension assembly) or proximity (show everything 75mm from the suspension assembly) and the relevant 3D model data was fetched in real time and visually displayed within the context of the full vehicle. In addition, a core capability of 4GD are "recipes," which is a way of capturing any of these searches so they are readily on hand for repetitive use, Sicking said. "Think of it as an efficient way to find information and replay it," he said.
Between 4GD, HD-PLM, Active Workspace, and Siemens' supercharged strategy to finely tune Teamcenter and the rest of its PLM portfolio to meet the needs of specific vertical industries like shipbuilding and A&D, company execs say there is far more work to be done to get PLM over the usability hurdle. "It's all tied to delivering the kind of value its customers need to drive innovation, shorten product development cycles, and facilitate global collaboration," said Chuck Grindstaff, Siemens PLM Software president.
Beth, I know what you mean when you say at the top of your article that PLM has been a tough pill to swallow. It seems that engineers and organizations have a hard time seeing the value of what they do now to help organize the information on a project for future use. We tend to think about the next deadline in our design process, not what the needs of the organization down the line. I was in one of those organizations that you mention. On the other hand, having that information available really makes you more effective over time.
I think that with products like this we are getting to a level of automation that takes some of the load off of the individual trying to solve a problem in the here and now. That is the trade-off.
It's a royal pain, but it has to be done. Take firmware for mobile phones. PLM is absolutely necessary to handle firmware releases, do regression testing. Done wrong, and you have very, very angry customers.
What is truly needed is for Siemens to talk to and LISTEN to their customer base. While new buzz words like 4GD, HD-PLM and Active Workspace generate excitement from a sales perspective, alot of the issues with PLM are much more rudimentary and if addressed properly, the user base would be telling everyone they know why they can't live without this technology.
@Kdkimball: What are some of the critical problems you see with PLM ease of implementation? The interesting thing is Siemens says a lot of these new technologies are a result of listening to their customer base and their requirements. I'd be curious to see where you see the disconnects.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.